Effect of hybrid iterative reconstruction technique on quantitative and qualitative image analysis at 256-slice prospective gating cardiac CT.
prospective_cohort · Level II
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- Record sourced from PubMed, PMID 22200900.
- Also identified by DOI 10.1007/s00330-011-2361-6.
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Abstract
To evaluate the effect of hybrid iterative reconstruction on qualitative and quantitative parameters at 256-slice cardiac CT. Prospective cardiac CT images from 20 patients were analysed. Paired image sets were created using 3 reconstructions, i.e. filtered back projection (FBP) and moderate- and high-level iterative reconstructions. Quantitative parameters including CT-attenuation, noise, and contrast-to-noise ratio (CNR) were determined in both proximal- and distal coronary segments. Image quality was graded on a 4-point scale. Coronary CT attenuation values were similar for FBP, moderate- and high-level iterative reconstruction at 293 ± 74-, 290 ± 75-, and 283 ± 78 Hounsfield units (HU), respectively. CNR was significantly higher with moderate- and high-level iterative reconstructions (10.9 ± 3.5 and 18.4 ± 6.2, respectively) than FBP (8.2 ± 2.5) as was the visual grading of proximal vessels. Visualisation of distal vessels was better with high-level iterative reconstruction than FBP. The mean number of assessable segments among 289 segments was 245, 260, and 267 for FBP, moderate- and high-level iterative reconstruction, respectively; the difference between FBP and high-level iterative reconstruction was significant. Interobserver agreement was significantly higher for moderate- and high-level iterative reconstruction than FBP. Cardiac CT using hybrid iterative reconstruction yields higher CNR and better image quality than FBP. • Cardiac CT helps clinicians to assess patients with coronary artery disease • Hybrid iterative reconstruction provides improved cardiac CT image quality • Hybrid iterative reconstruction improves the number of assessable coronary segments • Hybrid iterative reconstruction improves interobserver agreement on cardiac CT.
Medical subject headings
- Algorithms
- Coronary Angiography
- Coronary Artery Disease
- Radiographic Image Interpretation, Computer-Assisted
- Tomography, X-Ray Computed